Optimization of a regenerative blower to enhance aerodynamic and aeroacoustic performance

Abstract

A multi-objective optimization was performed to simultaneously enhance the aerodynamic and aeroacoustic performance of a side channel-type regenerative blower. The aerodynamic characteristics of the regenerative blower were investigated numerically using threedimensional steady and unsteady Reynolds-averaged Navier-Stokes analysis with a shear stress transport turbulence model. On the basis of the aerodynamic sources extracted from the unsteady flow calculation, three-dimensional aeroacoustic analysis was implemented using a finite/infinite element method by solving the variational formulation of Lighthill’s analogy. Three design variables, viz., the ratio of blade height to impeller diameter, ratio of blade width to impeller diameter, and angle between inlet and outlet port, were selected as design variables, and the efficiency and sound pressure level at the design point of the blower were selected as objective functions for the optimization. These two objective functions were estimated numerically through three-dimensional aerodynamic and aeroacoustic analyses at the design points sampled by Latin hypercube sampling in the design space. Pareto-optimal solutions were obtained using a hybrid multi-objective evolutionary algorithm coupled with radial basis neural network models as surrogates of the objective functions. Three arbitrarily selected optimum designs of the regenerative blower show significant increases in efficiency and reductions in sound pressure level compared to a reference design.